Kukedlc_-_NeuralContamination-7B-ties-gguf

Quantization made by Richard Erkhov.

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NeuralContamination-7B-ties - GGUF

• Model creator: https://huggingface.co/Kukedlc/
• Original model: https://huggingface.co/Kukedlc/NeuralContamination-7B-ties/

Original model description:

tags:

• merge
• mergekit
• lazymergekit
• yam-peleg/Experiment26-7B
• Kukedlc/NeuralSirKrishna-7b
• automerger/YamShadow-7B base_model:
• yam-peleg/Experiment26-7B
• Kukedlc/NeuralSirKrishna-7b
• automerger/YamShadow-7B license: apache-2.0

---

NeuralContamination-7B-ties

NeuralContamination-7B-ties is a merge of the following models using LazyMergekit:

• yam-peleg/Experiment26-7B
• Kukedlc/NeuralSirKrishna-7b
• automerger/YamShadow-7B

🧩 Configuration

models:
  - model: yam-peleg/Experiment26-7B
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: Kukedlc/NeuralSirKrishna-7b
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
  - model: automerger/YamShadow-7B
    parameters:
      density: 0.33
      weight:
        - filter: mlp
          value: 0.5
        - value: 0
merge_method: ties
base_model: liminerity/M7-7b
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/NeuralContamination-7B-ties"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

Genetic